Exploring equine therapy for people with dementia in long‐term care homes
Bibliographic record
Abstract
BACKGROUND: Equine(horse)-therapy or equine-assisted activities have been found to reduce stress, improve quality of life, and promote autonomy for people with dementia in long term care (LTC). In 2024, the [Walkabout Farm Therapeutic Riding Association Inc] in Ontario, Canada, recently launched a new program called R.E.A.P. (Recreational Equine Assisted Participaction). This program provides older adults in LTC homes full sensory engagement through interactions with horses, including petting, grooming, walking and feeding. Sessions, led by trained facilitators, last approximately 45 minutes and are hosted indoors at LTC homes, or on-site at Walkabout Farm. To date, no evaluation of equine-assisted activities for people with dementia living in LTC exists in Canada. The purpose of this study is to explore the feasibility, acceptability, and observed effects R.E.A.P. in LTC. METHOD: The research design consists of qualitative description with quantitative data collected in terms of feasibility (i.e., number of sessions provided per resident per week, length of sessions) and observed effects (i.e., engagement with the horses/stimuli; interactions between residents, caregivers, and staff). Research staff collected feasibility and observation data during the R.E.A.P. sessions. Data collection occurred in person either at the Walkabout Farm or at the LTC home. Interviews with residents and staff occurred in person, by phone or by videoconferencing (i.e., Zoom). Descriptive statistics were used for quantitative statistics and direct content analysis for the interview data. RESULT: A total of 12 participants completed the study including 3 staff members and 9 residents. None of the participants refused to participate in the sessions. Out of the 34 sessions delivered, residents were very attentive to attentive towards the horses (79%) and talked with the horses during the sessions (88%). Findings from the interviews revealed that sessions helped to foster relationships between residents, the horses, and staff, created emotional connection for residents, elicited enjoyment, and promoted reminiscing. CONCLUSION: The R.E.A.P. program demonstrated meaningful benefits to residents in LTC, including enhanced emotional well-being, social engagement and quality of life. These findings highlight the potential of equine therapy in enriching and supporting the well-being of residents in LTC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".